Development and validation of a survival prediction model and risk stratification for pancreatic neuroendocrine neoplasms

Z Lu; T Li; C Liu; Y Zheng; J Song

doi:10.1007/s40618-022-01956-7

Development and validation of a survival prediction model and risk stratification for pancreatic neuroendocrine neoplasms

J Endocrinol Invest. 2023 May;46(5):927-937. doi: 10.1007/s40618-022-01956-7. Epub 2022 Nov 17.

Authors

Z Lu^#¹, T Li^#^{2

3}, C Liu¹, Y Zheng^{1

3}, J Song⁴

Affiliations

¹ Department of General Surgery, Department of Hepato-Bilio-Pancreatic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, NO. 1 DaHua Road, Dong Dan, Beijing, 100730, People's Republic of China.
² National Center for Clinical Laboratories, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 Dahua Road, Dongcheng District, Beijing, 100730, People's Republic of China.
³ Graduate School, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
⁴ Department of General Surgery, Department of Hepato-Bilio-Pancreatic Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, NO. 1 DaHua Road, Dong Dan, Beijing, 100730, People's Republic of China. jhaisong2003@126.com.

^# Contributed equally.

PMID: 36394822
DOI: 10.1007/s40618-022-01956-7

Abstract

Purpose: We explored risk variables associated with cancer-specific survival (CSS) in patients with pancreatic neuroendocrine neoplasms (PNENs) and created a network dynamic nomogram model to predict patient survival time.

Methods: A total of 7750 patients with PNENs were included in this analysis, including 134 with functional PNENs and 7616 with nonfunctional PNENs. Clinical feature and prognosis differences between functional and nonfunctional PNENs were compared. Independent prognostic factors affecting CSS were analyzed by univariate and multifactorial Cox regression. Nomogram and web-based prognosis prediction of PNENs were developed and validated by C indices, decision curve analysis, and calibration plots.

Results: Patients with functional PNENs were younger at diagnosis than those with nonfunctional PNENs. Functional PNENs had better prognoses than nonfunctional PNENs (5-year survival rates: 78.55% and 71.10%, respectively). Univariate and multifactorial Cox regression analyses showed that tumor infiltration (T), nodal metastasis (N), metastasis (M), tumor site, differentiation grade, age, marital status, and surgical treatment were independent prognostic risk factors for CSS, which were included in the prognostic nomogram and web-based prognosis calculator. The calibration plots and decision curve analysis showed that the nomogram had excellent prediction and clinical practical ability. The C indices for CSS in the training and validation cohorts were 0.848 (95% CI 0.838-0.8578) and 0.823 (95% CI 0.807-0.839), respectively. We scored all patients according to the nomogram and divided patients into three different risk groups. The prognosis of the low-risk population was significantly better than those of the middle- and high-risk populations based on Kaplan-Meier survival curve.

Conclusion: We analyzed the clinical features of PNENs and developed a convenient and web dynamic nomogram to predict CSS.

Keywords: Cancer-specific survival; Pancreatic neuroendocrine neoplasm; Prediction model; Risk factors; Risk stratification.

MeSH terms

Humans
Kaplan-Meier Estimate
Neuroendocrine Tumors* / diagnosis
Nomograms
Pancreatic Neoplasms* / diagnosis
Risk Assessment